2026-02-27 21:02:40
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Headlines are fixated on AI bubble skepticism, while NVIDIA’s numbers tell a story of a new world being built.
CEO Jensen Huang believes we officially moved past the era of experimental training and entered the era of the agentic inflection:
“In this new world of AI, compute equals revenues. Without compute, there’s no way to generate tokens. Without tokens, there’s no way to grow revenues. [...] I am certain at this point that we’ve reached the inflection point.”
Huang is framing NVIDIA’s chips not as a capital expense, but as the direct raw material (tokens) required for customers to make money.
The latest quarter highlights three structural pillars:
Tokenomics over CapEx: Compute is becoming a raw material. Because every AI-generated token (a word, a pixel, a line of code) has an immediate market price, higher performance-per-watt translates directly into higher net margins per token.
Systems over Silicon: The bear case argues that specialized custom chips would steal the inference market. NVIDIA’s response is a shift from selling individual chips to delivering entire AI Factories. By controlling the networking fabric and the software stack, NVIDIA is ensuring that the cost-per-token remains lower on its platform.
Multi-Generational Overlap: For the first time, NVIDIA is ramping two flagship architectures—Blackwell and Rubin—simultaneously. With Rubin samples already shipping to customers this week, the roadmap is designed to capture the bulk of the estimated $4 trillion in infrastructure build-out coming this decade.
Let’s break down the quarter.
Today at a glance:
NVIDIA’s Q4 FY26.
Business highlights.
Key quotes from the call.
What to watch moving forward.
NVIDIA’s fiscal year ends in January, so they just reported Q4 FY26.
Data Center revenue remains off the charts, as illustrated below.
Revenue jumped +20% Q/Q and 73% Y/Y to $68.1 billion ($1.9 billion beat).
⚙️ Data Center +22% Q/Q and +75% Y/Y to $62.3 billion.
🎮 Gaming -13% Q/Q and +47% Y/Y to $3.7 billion.
👁️ Professional Viz +75% Q/Q and +159% Y/Y to $1.3 billion.
🚘 Automotive +2% Q/Q and +6% Y/Y to $0.6 billion.
🏭 OEM & Other -7% Q/Q and +28% Y/Y to $0.2 billion.
Gross margin was 75% (+2pp Y/Y).
Operating margin was 65% (+4pp Y/Y).
Non-GAAP operating margin was 68% (+1pp Y/Y).
Non-GAAP EPS $1.62 ($0.08 beat).
Operating cash flow +118% Y/Y to $36.2 billion.
Free cash flow +58% Y/Y to $34.9 billion.
Cash and cash equivalents: $62.6 billion.
Debt: $8.5 billion.
Revenue +15% Q/Q and +77% Y/Y to $78.0 billion ($6.0 billion beat).
Gross margin 75% (flat Q/Q).
⚙️ Data Center is now 91% of the business: We are witnessing a fundamental shift from AI being a research project to a profit center.
⚡ King of inference: While bears argue that specialized chips (ASICs) might take share as the market moves from training to inference. The Grace Blackwell servers are proving to be the most efficient infrastructure for running live AI tools.
🔌 Networking as a moat: Networking revenue hit $11 billion. This is the glue that prevents customers from easily switching to rival chips. As clusters grow to millions of GPUs, the complexity of the networking fabric becomes a structural barrier to entry for competitors.
🎮 Gaming faces a supply squeeze: Revenue fell 13% Q/Q to $3.7 billion. While some of this is seasonal, the bigger story is the global shortage of memory chips. NVIDIA is currently prioritizing its high-margin Data Center business for these scarce components, leaving the Gaming division supply-gated for the foreseeable future.
👁️ Professional Visualization was the surprise star: It was the fastest-growing segment this quarter, jumping 75% Q/Q to $1.3 billion. This was driven by a massive enterprise refresh cycle as companies upgrade to Blackwell-based workstations to run AI agents and industrial digital twins locally rather than in the cloud.
📈 Margins are the ultimate lie detector: Despite the complexity of ramping liquid-cooled Blackwell racks and the surging cost of memory chips, gross margin improved to 75.2%. If demand were softening or competition were biting, this would be the first place we would see scuff marks. The warning of a "very tight" supply for the next few quarters could shake things up.
🔮 The $78 billion outlook: Q1 FY27 guidance was a massive $6 billion beat over analyst estimates. But the market’s tepid reaction proves that NVIDIA is now held to a very high standard. Some bulls were whispering for $80 billion, and any hint of a supply ceiling (like the memory crunch) is enough to make investors pause.
Big picture: NVIDIA’s engine is now powered by the Blackwell Ultra refresh, the explosive networking growth, and the agentic transition. With $95 billion in supply-related commitments on the books, NVIDIA is already manufacturing the next two years of the AI cycle.
The market is increasingly focused on the cozy relationship between NVIDIA and its largest customers. With nearly $97 billion in annual free cash flow, NVIDIA is becoming the venture capitalist of the AI age.
By participating in OpenAI’s latest $30 billion round and deepening ties with Anthropic and CoreWeave, NVIDIA ensures that the most advanced AI models remain optimized for CUDA. Critics argue that NVIDIA is funding its own customers.
Jensen Huang defended this by highlighting the diversity of the customer base. Hyperscalers now account for only 50% of revenue, and growth is shifting toward sovereign AI and enterprise ISVs. The circular risk is diluted as the ecosystem broadens.
He also doubled down on the idea that customers must keep spending to grow. It captures the tension of this moment. NVIDIA sees a new industrial revolution, while some on Wall Street see a CapEx binge.
A more immediate threat emerged recently, as some of NVIDIA’s largest customers became shareholders in a competitor.
Meta just announced a multi-generation agreement worth more than $100 billion to deploy up to 6 gigawatts (GW) of AMD compute capacity. To secure this capacity, AMD issued Meta performance-based warrants for up to 160 million shares—roughly a 10% equity stake in AMD.
It is a carbon copy of the OpenAI-AMD pact signed in late 2025, which also included a 6 GW commitment and a 10% equity incentive.
By aligning their financial interests with AMD, two of NVIDIA’s most important allies are now directly incentivized to see AMD’s MI450 architecture succeed. For every gigawatt they deploy, they not only solve their supply chain bottleneck, but they also potentially unlock billions in capital appreciation from their AMD holdings. They are ecosystem partners with a vested interest in a multi-polar GPU market.
The market is valuing NVIDIA as if China is permanently zero. That embeds an option into the stock.
The Trump administration’s decision to allow small-scale H200 shipments comes with a US inspection requirement and a 25% tariff. This effectively makes NVIDIA chips the most expensive way to build AI in China.
CFO Colette Kress was clear that they are guiding for $0 revenue from China Data Center compute. This conservative guidance means any surprise approval or easing of these inspections represents an upside. NVIDIA is currently winning without China.
Check out the earnings call transcript on Fiscal.ai here.
“The wave that we’re seeing now is the agentic AI inflection [...] and it literally happened in the last couple of two, three months. [...] The agents are super smart, they’re solving real problems. Coding is obviously supported by agentic systems now.”
The latest catalyst is the shift from chatbots to autonomous agents that “run for minutes to hours” and consume massive amounts of compute.
“Every time you cross a dielet, you have to cross an interface. Every time you cross an interface, you add latency, you add power unnecessarily. [...] The dielet tax shows up in the architecture effectiveness of the competitors.”
Jensen is defending NVIDIA’s monolithic design (single piece) as a physical advantage in power efficiency that competitors using multi-chiplet designs can’t easily match. His bet is that architectural purity beats modular flexibility at hyperscale.
NVDA has been mostly flat in the past 6 months, a period of consolidation. The latest 13F filings for Q4 2025 showed that some funds were still buying, such as Altimeter and Atreides. The stock remains one of the most widely held names, although many funds are still underexposed relative to its nearly 8% weight in the S&P 500.
At ~27x forward earnings, NVIDIA trades mostly in line with the rest of Big Tech. But with EPS surging 67% Y/Y, you could certainly argue it looks cheap. NVIDIA’s growth is supply-constrained. That means quarter-to-quarter noise matters less than understanding how long this cycle can run and what the business looks like when demand normalizes.
If you’re a regular reader, you already know the stakes:
Inference momentum: Will NVIDIA’s full-stack strategy (Networking + Vera CPUs) protect its 75% margins against the rising tide of custom hyperscaler chips?
Memory bottleneck: Watch for any signs that the memory supply chain is loosening. With Micron exiting the consumer chip business and Steam running out of handhelds, NVIDIA’s Gaming rebound depends entirely on the availability of RAM.
Rubin cadence: Jensen confirmed Rubin is already in production. Any delay in the Blackwell-to-Rubin transition could create a demand air pocket that the market isn’t prepared for.
China visibility: NVIDIA is maintaining a zero-China baseline. Any revenue recognized through the new inspection-based licenses would be a pure upside surprise to the current stock price.
Power-to-token ratio: As data centers hit the 1-Gigawatt ceiling, performance-per-watt is the new ROI. NVIDIA’s lead depends on being the most energy-efficient AI factory on the planet.
In a token economy, efficiency is profit.
That’s the battlefield NVIDIA intends to dominate.
That’s it for today!
Happy investing!
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Disclosure: I own AAPL, AMD, AMZN, GOOG, META, and NVDA in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with App Economy Portfolio members.
Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.
2026-02-25 08:10:17
Welcome to the Premium edition of How They Make Money.
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We’re tracking the early standouts today.
Coming up later this week: NVIDIA, Salesforce, Snowflake, and more.
Anthropic’s announcement of Claude Code Security on Friday has triggered a sell-off in the last few software stocks that had been holding up. The tool scans codebases and patches vulnerabilities like a human researcher. It wiped billions in value off security leaders like CrowdStrike and Okta. It’s the latest reminder that if you are a software stock in 2026, you are only one Anthropic blog post away from calamity.
While Anthropic is busy terrifying SaaS investors, the company itself relies on Workday to manage its own global operations. It might surprise you since Klarna famously ditched the software in 2024 to build its own alternative internally. It seems even the creators of the world’s most advanced agents still need a reliable place to file their expenses and manage their headcount.
It’s the delicious irony of this moment. The largest AI disruptors are still writing checks to the incumbents for their HR and finance stacks. The AI revolution is still being run on the very software it’s supposed to be replacing. But it probably won’t change the bear case, which ignores the numbers today and focuses on the disruption tomorrow.
Today at a glance:
👔 Workday: Funding the AI Pivot
🤝 MercadoLibre: Playing the Long Game
⚡️ Axon: Surprise 2028 Target
⛷️ Amer Sports: Salomon Expansion
🖨️ HP: PC Strength Overshadowed
🍕 Domino’s: Taking a Bigger Slice
🧬 Tempus AI: Scaling Data Advantage
🌊 DigitalOcean: Rule of 50 by 2027
💊 Hims & Hers: Legal Headwinds
🍿 AMC: Attendance Drops
Workday wrapped up FY26 (ending in January) with a fourth-quarter beat. But a soft outlook and a sudden CEO transition sent shares tumbling roughly 8% in after-hours trading. Q4 revenue rose 15% Y/Y to $2.53 billion ($10 million beat), and non-GAAP EPS reached $2.47 ($0.15 beat). Subscription revenue was the main driver, rising 16% Y/Y to $2.36 billion.
WDAY was already in a tough spot, with shares trading nearly 60% off their peak. The market reacted poorly to the company’s fiscal 2027 guidance. Workday expects full-year subscription revenue growth to slow to 12% to 13% ($9.925 billion to $9.950 billion), missing the $10 billion consensus estimate. This outlook matched the growth in subscription revenue backlog, up 12% Y/Y to $28.1 billion.
Adjusted operating margins are also forecasted to dip to 30% in FY27 (down from 30.6% in Q4 FY26) as the company prioritizes AI investments over near-term margin expansion. Management also noted that large enterprise deals in the federal and healthcare sectors are taking longer to close.
Workday is spending heavily to buy its way into immediate AI capabilities. In quick succession, they integrated Sana (conversational AI and enterprise connectivity) and acquired Pipedream (a startup with tools to connect AI agents to external services), following the recent close of Paradox (an AI recruiting platform).
The ROI on this approach is starting to show. In Q4 alone, Workday generated over $100 million in new Annual Contract Value (ACV) strictly from emerging AI products (over 100% Y/Y growth). Overall Annual Recurring Revenue (ARR) from these AI solutions has now crossed $400 million. Internally, the company has completely overhauled its engineering infrastructure. Over 75% of Workday's software engineers now use AI coding assistants, resulting in more than 50% of newly committed code being AI-generated and boosting overall engineering output by 22%.
The quarter featured a major leadership change. Carl Eschenbach stepped down earlier this month, bringing co-founder Aneel Bhusri back to the CEO role. Bhusri used the earnings call to push Workday’s Chapter Four strategy, focusing heavily on integrating agentic AI directly into HR and finance workflows. To monetize this shift, the company is transitioning to a consumption-based Flex Credits pricing model for its AI offerings.
These clear AI tailwinds are not doing much for the stock. For now, the market is keeping WDAY in the penalty box and isn’t giving the new management team the benefit of the doubt. The company is trading at a forward EBITDA multiple below 10x.
2026-02-21 23:02:20
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📊 Monthly reports: 200+ companies visualized.
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Today at a glance:
🛒 Walmart: E-Commerce Leads the Way
🛩️ Airbus: Engine Dispute Dents Outlook
⚙️ Analog Devices: Industrial Power Ahead
🏝️ Booking: Stacking Savings
💡 Cadence: AI Amplifies the Backlog
💼 Moody’s: AI Resilience
🥡 DoorDash: Local Commerce OS
🎤 Live Nation: A $25 Billion Encore
🌎 Global Payments: Pure-Play Pivot
🛵 Grab: Critical Proof Point
💻 Lenovo: AI Boom Meets Memory Crunch
🎨 Figma: AI Fears Fade For Now
💳 Klarna: Banking Pivot
📦 Etsy: Pure-Play Pivot
🛍️ Global-e: Scaling Through Intelligence
Walmart just reported its January quarter (Q4 FY26), and revenue grew 6% Y/Y to $190.7 billion ($2.4 billion beat). Adjusted EPS narrowly topped expectations, marking a resilient holiday season despite a compressed shopping window.
Walmart US comps rose 4.6%, matching consensus, driven by a 2.6% increase in transactions. International sales were a standout, climbing 11.5% to $35.9 billion, led by strength in China, Mexico (Walmex), and India (Flipkart).
The steady shift toward digital continued:
E-commerce momentum: Global e-commerce sales grew 24%, now representing 23% of total revenue. In the US, online sales jumped 27%, fueled by store-fulfilled delivery and a growing marketplace.
Profit diversification: High-margin streams (advertising and membership) now account for nearly one-third of total operating income. Global advertising grew 37% (bolstered by VIZIO), while membership revenue surged over 15%.
AI integration: The AI shopping assistant, Sparky, is showing early success. Customers using the tool have an average order value 35% higher than those who do not.
The Walmart US boss, John Furner, officially took over as CEO on February 1, 2026. Furner inherits a company with a healthy balance sheet, nearly $15 billion in free cash flow in FY26, and a massive new $30 billion share buyback authorization.
Inventory management remains a major win, with levels growing at just half the rate of sales growth, thanks to automation in 60% of US stores and 50% of fulfillment centers. This efficiency helped adjusted operating income grow 10.5%, significantly outpacing sales growth.
Despite the beat, shares saw some volatility due to a cautious FY27 outlook that missed analyst targets:
Sales growth: 3.5%–4.5% (vs. 5% consensus).
Adjusted EPS: $2.75–$2.85 (vs. $2.97 consensus).
Management cited an unpredictable macro environment, noting a widening spending gap between high-income households (earning over $100k) and stretched low-income consumers. While Walmart continues to gain share across all cohorts, it is bracing for potential headwinds from tariff-related cost pressures and normalized pricing.
Airbus closed FY25 with a mixed quarter, beating on the bottom line but missing on revenue and delivering a disappointing outlook.
Q4 revenue rose 5% Y/Y to €26.0 billion (€0.8 billion miss), while GAAP EPS was €3.27 (€0.50 beat). For the full year, the company saw revenue rise 6% Y/Y to €73.4 billion and posted a record Adjusted EBIT of €7.1 billion. Airbus delivered 793 commercial aircraft in FY25, backed by a backlog of 8,754 jets.
However, shares tumbled following an unusually public and combative rebuke of engine supplier Pratt & Whitney (an RTX subsidiary). CEO Guillaume Faury explicitly accused Pratt of failing to meet its contractual commitments for engine deliveries, prioritizing the maintenance of existing airline fleets over supplying new jets. Airbus announced it has formally triggered a dispute clause in its contract to seek compensation for lost business.
As a direct result of the engine shortage, Airbus significantly slashed its 2026 production guidance. The company now expects to deliver roughly 870 commercial aircraft in 2026 (well below the Wall Street consensus of 900+ jets) and generate an Adjusted EBIT of around €7.5 billion (missing the €8.2 billion expectation). The long-held goal of producing 75 A320s per month has been delayed yet again, now targeted for the end of 2027.
2026-02-20 21:02:48
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AI agents threaten to compress white-collar workflows, and markets have responded by repricing the entire sector. Over the past five years, the WisdomTree Cloud Computing ETF (WCLD) was cut in half, while the Nasdaq-100 (QQQ) has nearly doubled. Since our breakdown of the SaaSpocalypse last month, software stocks have dropped another 10%.
When narratives shift, markets rarely discriminate.
But look closer. A dispersion is emerging between those who sell human productivity and those who capture the rise in workloads.
Investors have questioned everything from seat-based pricing to enterprise IT budgets. Some predict agentic disintermediation on the horizon, with near-term earnings merely a distraction and terminal values revised toward zero.
The comparison to the printed press in the 2000s is common. But that analogy confuses disruption with extinction. The New York Times (NYT), once cited as a casualty of the Internet, is up nearly 6x over the past decade and has doubled the returns of the S&P 500.
Markets tend to extrapolate the present trend, bearish or bullish. But software is not a monolith.
The repricing underway is far more selective than it appears at first.
For years, software was treated as one category:
Recurring revenue.
High gross margins.
Scalable business models.
Favoring growth over profitability.
Whether it was CRM or cybersecurity, most companies benefited from the same secular tailwinds: cloud migration, digital transformation, and expanding enterprise IT budgets.
AI is forcing a more nuanced distinction.
Some software businesses scale primarily with headcount. Revenue grows as customers hire employees and provision more seats. When hiring slows or when automation reduces the need for certain roles, that growth engine weakens.
Others scale with infrastructure usage. Their revenue increases as compute workloads rise, traffic expands, systems grow more complex, and security risks multiply. AI does not compress those forces. It intensifies them.
The distinction matters because these two models respond differently to AI.
Application software is tied to labor intensity.
Infrastructure software is tied to computational intensity.
As AI adoption increases, those forces move in opposite directions. Application software is a tax on labor. Infrastructure software is a tax on compute.
Seat-based pricing may face pressure as workflows become more automated. In contrast, software linked to usage, traffic, and system complexity can expand alongside AI-driven workloads.
If AI increases traffic and system complexity, it also increases risk.
Every new API endpoint, cloud workload, or AI-powered workflow expands the potential attack surface. As enterprises embed AI into products and internal operations, the need for visibility and protection grows alongside it.
Palo Alto Networks (PANW) remains the largest ‘pure-play’ cybersecurity company today. Its software helps organizations secure networks, cloud environments, and endpoints across increasingly distributed systems.
Security budgets tend to behave differently from productivity budgets. Companies may slow hiring or delay software upgrades, but they rarely reduce protection when systems become more complex.
The most recent quarter reinforced this dynamic. PANW just reported Q2 FY26 results (January quarter). Revenue grew 15% to $2.6 billion, as enterprises continued consolidating vendors and expanding their security footprint.
The company has steadily improved its operating margin over the past five years, reaching a new high of 14% in the past 12 months (15% in Q2).
The core Next-Generation Security (NGS) Annual Recurring Revenue (ARR) expanded 33% to $6.3 billion, while the RPO backlog rose 23% Y/Y to $16.0 billion. For perspective, the NGS business is larger and growing faster than CrowdStrike’s entire ARR.
Management noted that 110 customers adopted multiple Palo Alto products rather than a single standalone tool. It favors unified platforms, specifically Strata (Network Security), Prisma (Cloud Security), and Cortex (Security Operations/AI-driven SOC)
This shift is increasingly driven by AI, as customers look to consolidate their security stacks to defend against more sophisticated, autonomous threats.
The quarter was defined by aggressive M&A activity aimed at rounding out the ecosystem:
Identity & observability: The company recently closed its $25 billion acquisition of CyberArk and its $3.3 billion deal for Chronosphere. These additions are expected to be the primary growth engines for the remainder of the fiscal year.
Agentic AI: Palo Alto announced its intent to acquire Koi, an Israeli startup focused on agentic endpoint security. The goal is to secure autonomous AI agents and scripts that often operate outside traditional security visibility.
Product momentum: Prisma AIRS (AI Security) tripled its customer count to over 100 in just a few quarters, while the SASE business surpassed $1.5 billion in ARR.
Palo Alto just raised its revenue and ARR outlook substantially, but the increase is largely attributable to two recent acquisitions. A lowered EPS guidance reflected higher memory and storage costs, as well as share dilution from the massive CyberArk transaction. The stock fell after earnings as investors weighed the revenue surge against the near-term margin pressure and acquisition costs.
The company reiterated its long-term FY30 goal of $20 billion in NGS ARR and its FY28 target of 40%+ free cash flow margins (from mid-30s today).
If AI agents become the new users of the web, they still rely on the same foundational layer, the network.
Cloudflare (NET) operates at that layer. It routes traffic, secures endpoints, mitigates attacks, and increasingly runs compute at the edge. Unlike application software that scales with employees, network software scales with requests and workloads.
AI increases both.
As companies deploy AI features, API calls multiply. Systems become more distributed. Traffic patterns grow less predictable. Security risks expand. Each of those forces drives demand for routing, protection, and edge execution.
This is why Cloudflare’s growth trajectory has diverged from many application software businesses. Its revenue is tied less to hiring cycles and more to digital activity itself. The company’s revenue growth re-accelerated to its fastest pace in nearly three years.
In a world of agentic workflows and machine-to-machine communication, the network layer becomes more central, not less.
If the network layer moves traffic, the observability layer explains what happens after that traffic arrives.
Datadog (DDOG) provides monitoring across logs, metrics, traces, and increasingly AI workloads themselves. In modern cloud architectures, where applications are distributed across services and regions, observability is mission-critical.
AI adds another layer of complexity. Models generate new workloads, services interact in more dynamic ways, and latency or performance issues carry greater consequences. As systems grow more intricate, visibility becomes more valuable.
The largest operating expense for most software businesses is sales & marketing (S&M). In contrast, Datadog is a typical case of product-led growth. Most of the gross profit is plowed back into R&D expenses.
Unlike seat-based application software, observability tools scale with infrastructure usage. More services, more traffic, and more compute translate into greater monitoring demand. This explains why Datadog has reported a steady increase in multi-product adoption, with 18% of its customers using over 8 products.
This dynamic helps explain why certain infrastructure-oriented software companies are seeing stabilization or re-acceleration even as parts of the broader SaaS universe remain under pressure.
As Datadog CEO Olivier Pomel noted last week, AI-native customers are “growing significantly faster than the rest of the business” as their workloads move into production and expand across users and tokens.
The keyword is production. As experimental AI deployments scale into real systems, monitoring demand scales with them.
If the divide between application and infrastructure software continues to widen, it should show up in the numbers.
Watch for:
Usage-based revenue trends: Companies tied to compute, traffic, and cloud workloads should see stabilization or acceleration before seat-based vendors.
Net retention dynamics: Infrastructure software should benefit from expanding workloads even if hiring remains muted.
Security and observability budgets: As AI adoption grows, spending on protection and monitoring should prove more resilient than spending on productivity tools.
Cloud CapEx and workload growth: If hyperscaler investment remains elevated, infrastructure-linked software stands to benefit.
New business models: Monitor shifts toward usage-based services or flat-tier subscriptions based on the service delivered.
The broader narrative may still treat software as one category. But the economics underneath are diverging.
And markets eventually reprice divergence.
That’s it for today!
Stay healthy and invest on!
Thanks to Fiscal.ai for being our official data partner. Create your own charts and pull key metrics from 50,000+ companies directly on Fiscal.ai. Start an account for free and save 15% on paid plans with this link.
Disclosure: I own PANW, DDOG, and NET in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with members.
Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.
2026-02-18 09:36:04
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Every quarter, funds managing over $100 million must disclose their portfolios, offering a rare glimpse into the minds of elite investors.
The latest 13F filings capture trades from October 1 to December 31.
Q4 was defined by an AI infrastructure arms race and massive CapEx commitments from Big Tech. The market has increasingly concentrated in a handful of dominant players as rate-cut expectations shifted into 2026.
Against that backdrop, super investors repositioned into year-end, just before software sentiment began to crack in early 2026.
Some doubled down on winners, others quietly rotated.
Let’s see where the smart money leaned.
Today at a glance:
Hedge funds’ strategies.
Top buys and top holdings in Q4.
A surprisingly popular buy.
Implications for individual investors.
Before we dive into 13Fs, a quick reminder: blindly copying hedge fund trades is a terrible strategy.
Investing is like shooting 3-pointers. Even Steph Curry, the greatest shooter ever, misses more than half the time. There are no sure bets, even for the pros.
Your behavior matters more than your portfolio. As Peter Lynch said, “Know what you own and why you own it.”
Conviction is what helps you hold through volatility. And conviction comes from doing your own work, not borrowing someone else’s.
As Ian Cassel puts it:
“You can borrow someone else’s stock ideas but you can’t borrow their conviction. […] Do the work so you know when to sell. Do the work so you can hold. Do the work so you can stand alone.”
Some limitations of 13F filings:
Omit short positions and cash reserves.
Offer a partial view, leaving out smaller funds.
Exclude non-US equities, bonds, and commodities.
Can be dated, given their submission 45 days after the quarter.
With all this said, let’s see what top funds were buying and holding in Q4.
Hedge funds are financial powerhouses known for flexible, aggressive strategies designed to beat the market.
Here’s what typically shapes their moves:
Market conditions: Long in bull markets, defensive in bear markets.
Sector trends: Shifts in regulation or consumer behavior steer capital.
Fundamentals: Strong earnings, free cash flow, and leadership matter.
Macro factors: Rates, inflation, and geopolitics influence positioning.
Quant models: Some lean on proprietary algorithms to find an edge.
Risk management: Diversification, hedging, and position sizing.
Investor sentiment: Fear and greed create mispriced opportunities.
Still, it doesn’t always work out.
The Global X Guru ETF (GURU), built to track top hedge fund holdings, has underperformed the S&P 500 since its inception in 2012, even before fees.
And those fees matter. The classic “2 and 20” model (2% of assets + 20% of gains) can significantly reduce returns. It's no wonder that many individual investors are opting for simpler, lower-cost strategies.
Our partners at Fiscal.ai gather the data on Super Investors and visualize their portfolio for you. Pick your favorite investors and see how their holdings have evolved.
In early 2020, just before the COVID market turmoil, I curated a list of 20 top-performing hedge funds using TipRanks data. The selection focused on alpha relative to the S&P 500, and I also included a few funds frequently featured in my social feeds and podcast rotation. It’s not perfect, but it remains a solid directional filter.
The 10 stocks below represent half of the top holdings listed:
🤖 AI infrastructure: META, NVDA, TSM, GEV.
☁️ Hyperscalers: AMZN, MSFT, GOOG.
📦 Global commerce: SHOP, MELI, SE, V.
Amazon remains by far the most widely held stock at the top of these portfolios, appearing in 12 of the 20 funds. Also, note that Apple is entirely absent despite being the second-largest company by market cap globally. You also won’t find Tesla here.
This list of holdings doesn’t change much from one quarter to the next, so let’s turn to the more actionable insights with the new movements in Q4.
2026-02-14 23:02:19
Welcome to the Saturday PRO edition of How They Make Money.
Over 290,000 subscribers turn to us for business and investment insights.
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📊 Monthly reports: 200+ companies visualized.
📩 Tuesday articles: Exclusive deep dives and insights.
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📩 Saturday PRO reports: Timely insights on the latest earnings.
Today at a glance:
🌐 Cisco: AI Boom & Margin Squeeze
🛍️ Shopify: The Cost of Agentic Growth
⚙️ Applied Materials: AI Ramp Begins
🧬 AstraZeneca: Oncology Drives the Beat
🥤 Coca-Cola: Rare Miss & A New Boss
🍟 McDonald’s: The Grinch Wins Christmas
📶 T-Mobile US: Guidance to the Rescue
🌐 Arista Networks: AI Validation
📱 AppLovin: The Great Disconnect
🎮 NetEase: Hitting the Brakes
🪶 Robinhood: The Crypto Fade
🛖 Airbnb: Growth Acceleration
✈️ Expedia: B2B Powerhouse
🏨 Marriott: Credit Card Kicker
🏨 Hilton: Guidance Gloom
👜 Hermès: The Untouchable
💄 L'Oréal: Luxe Drag But Derma Shine
🧣 Kering: Not as Bad as Feared
🏎️ Ferrari: Luxury of Less
🚙 Ford: Tariff Shock
☁️ Cloudflare: The Agentic Internet
🐶 Datadog: Best in Show
📈 Coinbase: Cyclical Reset
💳 Adyen: Growth Reset
💳 Fiserv: Hard Reset
🌭 Kraft Heinz: The Great Pause
🍔 RBI: Burger King Remodels Slow
💬 Twilio: AI Infrastructure Pivot
🍞 Toast: Profitable Pivot
🏠 Zillow: Rentals Boom But Profit Gloom
👑 DraftKings: Prediction Gamble
📌 Pinterest: Exogenous Shock
📢 HubSpot: Agentic Pivot Pays Off
🚘 Lyft: Headline Shock
🏴 Klaviyo: Autonomous Growth
📆 Monday.com: Guidance Trap
Cisco’s Q2 FY26 (January quarter) revenue accelerated to 10% Y/Y growth, hitting $15.3 billion ($230 million beat), while adjusted EPS came in at $1.04 ($0.02 beat).
The AI infrastructure momentum continued. AI orders from hyperscalers jumped to $2.1 billion in the quarter (up from $1.3 billion in Q1). Consequently, management raised its FY26 AI orders outlook to exceed $5 billion, driven by demand for its Silicon One chips and 800G optical pluggables.
Networking revenue surged 21% Y/Y, fueled by the hyperscaler spend and a campus refresh cycle. However, Security revenue declined 4%, continuing to lag as the portfolio transitions and integrates Splunk (acquired in March 2024).
Despite the top-line beat and accelerating AI story, shares fell post-earnings due to a disappointing margin outlook. Management guided Q3 adjusted gross margins to ~66% (well below the 68.2% consensus), citing surging memory chip prices that are inflating costs faster than Cisco can raise prices.
Cisco raised its full-year FY26 guidance again, now forecasting revenue of $61.2–$61.7 billion (up from $60.2–$61.0 billion). The company also raised its quarterly dividend to $0.42 per share. While the AI growth thesis is playing out faster than expected, investors are now grappling with the near-term profitability tax of that growth.
Shopify closed FY25 with a high-octane quarter that highlighted a deepening tug-of-war between growth and profitability.
Q4 revenue surged 31% Y/Y to $3.7 billion ($80 million beat), and Gross Merchandise Volume (GMV) climbed 31% to $124 billion. For the full-year, revenue rose 30% Y/Y to $11.6 billion. This marked the highest annual revenue growth since the COVID boom of 2021.
The stock plunged despite the top-line beat and the authorization of a new $2 billion share buyback. The culprit was the bottom line. Adjusted EPS of $0.48 slightly missed the $0.51 consensus, and management guided for Q1 Free Cash Flow margins to dip into the “low-to-mid teens” (down from 19% in Q4) as they aggressively ramp up spending on AI. Sounds familiar?
The company is betting heavily on the Agentic Internet, launching the Universal Commerce Protocol (UCP) in collaboration with Google to allow AI agents to shop on behalf of consumers. While management argued that “no one is better positioned” for this shift, investors are punishing the immediate margin compression required to build this infrastructure.
On the bright side, the core business is firing on all cylinders. B2B GMV exploded 84% Y/Y, International revenue grew 36%, and the company guided for Q1 revenue growth in the “low-thirties”—significantly ahead of the 25% consensus.